Minimizing within Convex Bodies Using a Convex Hull Method

We present numerical methods to solve optimization problems on the space of convex functions or among convex bodies. Hence convexity is a constraint on the admissible objects, whereas the functionals are not required to be convex. To deal with this, our method mixes geometrical and numerical algorit...

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Bibliographic Details
Published in:SIAM journal on optimization 2005-01, Vol.16 (2), p.368-379
Main Authors: Lachand-Robert, Thomas, Oudet, Édouard
Format: Article
Language:English
Subjects:
Algorithms
Analysis of PDEs
Applied mathematics
Approximation
Convex analysis
Mathematics
Methods
Numerical analysis
Optimization
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Summary:We present numerical methods to solve optimization problems on the space of convex functions or among convex bodies. Hence convexity is a constraint on the admissible objects, whereas the functionals are not required to be convex. To deal with this, our method mixes geometrical and numerical algorithms. We give several applications arising from classical problems in geometry and analysis: Alexandrov's problem of finding a convex body of prescribed surface function; Cheeger's problem of a subdomain minimizing the ratio surface area on volume; Newton's problem of the body of minimal resistance. In particular for the latter application, the minimizers are still unknown, except in some particular classes. We give approximate solutions better than the theoretical known ones, hence demonstrating that the minimizers do not belong to these classes.
ISSN:1052-6234
1095-7189
DOI:10.1137/040608039